Soheib Fergani

Performances improvement through an LPV/H ∞ control coordination strategy involving braking, semi-active suspension and steering Systems

This paper proposes a new multivariable design strategy for Global Chassis Control, using LPV/H∞ robust controllers of semi-active suspension, active steering and electro-mechanical braking actuators. The proposed solution is a two stages control scheme: on one hand, rear braking and front steering to enhance the vehicle yaw stability and the lateral dynamics, and on the other hand, semi-active suspensions to improve comfort and car handling performances. The main idea of the strategy is to schedule the 3 control actions (braking, steering and suspension) according to the driving situation evaluated by a specific monitor. The main result of this paper is to propose a “LPV” strategy that aims to enhance vehicle performances by generating a hierarchical activation of the 3 controllers in critical driving situations. Simulations are carried out on a complex full vehicle model equipped with Magneto-Rheological Dampers characteristics subject to critical driving situations. A comparison between the proposed “LPV” strategy with the “LTI” case confirms the effectiveness of the proposed control strategy.

A new LPV/H∞ Global Chassis Control through load transfer distribution and vehicle stability monitoring

This paper proposes a new multivariable LPV/H∞ Global Chassis Control (GCC) strategy, using suspension, active steering and electro-mechanical braking actuators. This new approach allows, by allocating the load transfer in the four corners of the vehicle, scheduling the suspensions actuators and so to enhance vertical performances. Also, through a consistent stability monitor, based on a slip dynamics supervision, the braking and the steering controllers are scheduled. The good distribution of the load transfer aims at tuning the suspensions in the four corners (either soft or hard), to improve the car holding. The stability index schedules the action of the braking and the steering actuators, to ensure a good coordination between those controllers. This strategy improves the car dynamics behavior and the vehicle stability. Simulations performed on a complex nonlinear full vehicle model, subject to critical driving situations, show the reliability and the robustness of the proposed solution.

A new LPV/ℋ ∞ semi-active suspension control strategy with performance adaptation to roll behavior based on non linear algebraic road profile estimation

This paper presents a new LPV/H∞ semi-active suspension control strategy for a commercial vehicle equipped with 4 Magneto-Rheological dampers. The proposed approach concerns road adaptation using on-line road profile identification based on a non linear algebraic observer with unknown input. Then, the suspensions forces distribution in each corner of vehicle is performed considering roll dynamics. In this LPV/H∞ strategy, 2 varying parameters are used to model the semi-active behaviour of the MR dampers, and 2 other ones, namely, the road roughness identification and roll dynamics, are considered for the road adaptation and the full vehicle vertical dynamics control. Different ISO road classes are used to test the efficiency of the on-line non linear algebraic road profile identification. Simulations scenarios, applied on a non linear full vehicle model, are used to evaluate the LPV/H∞ controller performances in term of passengers comfort and road holding improvement in different driving situations.

Global Chassis Control Using Coordinated Control of Braking/Steering Actuators

Automotive light vehicles are complex systems involving many different dynamics. On one side, vertical, roll and pitch behaviours are often related to comfort performances (indeed, roll is also linked to safety characteristics [23]). On the other hand, safety performances are mainly characterized by the longitudinal, lateral and yaw dynamics [38, 14]. In practice, these two behaviours are often treated in a decoupled may (the first dynamics are often related to suspensions systems while the second one to steering and braking systems). This chapter focuses on the safety problem, and more specifically, on lateral and yaw dynamics. It presents two close techniques to design robust gain-scheduled \(\mathcal{H}_\infty\) MIMO VDSC (Vehicle Dynamic Stability Controller), involving both steering and rear braking actuators. Both approaches aim at restoring the yaw rate of the vehicle as close as possible to the nominal motion expected by the driver. The specific framework of each of that approaches is given below.

Road Adaptive Semi-Active Suspension in an Automotive Vehicle using an LPV Controller

Abstract A novel road adaptive Linear Parameter-Varying (LPV) based controller for the semi-active suspension system of an automotive vehicle is proposed. The analysis is carried on the front-left Quarter of Vehicle (QoV) model generated via CarSim TM vehicle simulator. By using an on-line road roughness estimation, considered as a scheduling parameter, the proposed LPV/ℋ ∞ controller is designed to improve comfort and road holding. The road profile detector is based on the frequency and amplitude estimation of the road irregularities by using a Fourier analysis. An ℋ ∞ robust observer is designed to estimate the variables related to the QoV vertical dynamics, which are used to compute the road frequency and roughness. Different ISO road classes are used to evaluate on-line the proposed road identification algorithm. A Receiver Operating Characteristic (ROC) curve is used to monitor the performance of the roughness estimation; the results show that any road can be identified (at least 70% of success with a false alarm rate lower than 5%). The average error of road identification is 16.2%. Simulation results show that the proposed controller with road adaptation is capable to manage the trade-off between comfort and road holding. The road adaptive controller increases the comfort (35.8%) when the vehicle is driven on a road of bad quality, by considering an uncontrolled damper (passive suspension) as a benchmark. If the vehicle is driven on a smooth runway at high velocity, the proposed controller improves the road holding around 50%.

An

This paper is concerned with the design and analysis of a new multivariable LP V /H∞ (Linear Parameter Varying) robust control design strategy for Global Chassis Control. The main objective of this study is to handle critical driving situations by activating several controller subsystems in a hierarchical way. The proposed solution consists indeed in a two-step control strategy that uses semi-active suspensions, active steering and electro-mechanical braking actuators. The main idea of the strategy is to schedule the 3 control actions (braking, steering and suspension) according to the driving situation evaluated by a specific monitor. Indeed, on one hand, rear braking and front steering are used to enhance the vehicle yaw stability and lateral dynamics, and on the other hand, the semi-active suspensions to improve comfort and car handling performances. Thanks to the LP V /H∞ framework, this new approach allows to reach a smooth coordination between the various actuators, to ensure robustness and stability of the proposed solution, and to significantly improve the vehicle dynamical behavior. Simulations have been performed on a complex full vehicle model which has been validated using data obtained from experimental tests on a real Renault Megane Coupe. Moreover, the suspension system uses Magneto-Rheological dampers whose characteristics have been obtained through experimental identification tests. A comparison between the proposed LPV/H∞ control strategy and a classical LTI/H∞ controller is performed using the same simulation scenarios and confirms the effectiveness of this approach.This paper proposes a new multivariable linear parameter varying (LPV)/H∞ control strategy for global chassis control. The main objective is to handle critical driving situations by activating several subsystems (semi-active suspensions, active steering, and electromechanical braking actuators) in a hierarchical way. The main idea is to schedule the three control actions (braking, steering and suspension) according to the driving situation evaluated by a specific monitor. Indeed, on one hand, rear braking and front steering are used to enhance the vehicle yaw stability and lateral dynamics, and on the other hand, the semi-active suspensions are used to improve comfort and car handling performance. Due to the LPV/H∞ framework, this new approach allows a smooth coordination to be reached between the various actuators, to ensure robustness and stability of the proposed solution, and to significantly improve the vehicle dynamical behavior. Simulations have been performed on a complex full vehicle model, which has been validated using data obtained from experimental tests on a real Renault Mégane Coupé. Moreover, the suspension system uses magnetorheological dampers whose characteristics have been obtained through experimental identification tests. A comparison between the proposed LPV/H∞ control strategy and a classical linear time-invariant/H∞controller is performed using the same simulation scenarios and confirms the effectiveness of this approach.

\mbox{LPV}/\mathcal{H}_\infty

The road profile is one of the most important factors that determines the automotive vehicle performance; specially, when it is used to adapt the suspension features. Direct measurements of the road represent expensive solutions and are susceptible to be contaminated. This paper proposes a novel road profile estimation method based on classic vehicle measurements to online compute the road roughness and an ISO 8608 classification; all suspension variables used in the road estimation algorithm are obtained by an ℋ∞ robust observer. The method of road profile estimation is based on the frequency and amplitude estimation of the road irregularities using a Fourier analysis. Experimental results on the rear-left corner of a 1:5 scale vehicle have been used to validate the proposed road estimation method. Different ISO road classes online evaluate the performance of the road identification algorithm, whose results show that any road can be identified at least 70% of success with a false alarm rate lower than 5%; the average error of road identification is 17.5%. A second test with variable vehicle velocity shows the importance of the online frequency estimation to adapt the road estimation algorithm to any driving velocity, the road is correctly estimated with an error of 17%).

Integrated Vehicle Dynamic Controller

This paper proposes a LPV/ℌ∞ fault tolerant control strategy for roll dynamics handling under semi-active dampers malfunction. Indeed, in case of dampers malfunction, a lateral load transfer is generated, that amplifies the risks of vehicle roll over. In this study, the suspension systems efficiency is monitored through the lateral (or longitudinal) load transfer induced by a dampers malfunction. The information given by the monitoring system is used in a partly fixed LPV/ℌ∞ controller structure that allows to manage the distribution of the four dampers forces in order to handle the over load caused by one dampers malfunction. The proposed LPV/ℌ∞ controller then uses the 3 remaining healthy semi-active dampers in a real time reconfiguration. Moreover, the performances of the car vertical dynamics (roll, bounce) are adapted to the varying parameter given by the monitoring of the suspension system efficiency, which allows to modify online the damping properties (soft/hard) to limit the induced load transfer. Simulations are performed on a complex nonlinear full vehicle model, equipped by 4 magneto-rheological semi-active dampers. This vehicle undergoes critical driving situations, and only one damper is considered faulty at ones. The simulation results show the reliability and the robustness of the proposed solution.

Online road profile estimation in automotive vehicles

This paper proposes a study and a comparison between two efficient and relatively recent vehicle control dynamics strategies, namely, the non linear Flatness control strategy and the LPV/H∞ control strategy. The first one concerns a controller based on the differential algebraic flatness of non linear systems and an algebraic non linear estimation applied to commercial vehicles. The second one is a LPV/H∞ (Linear Varying Parameter with the H∞ norm) control using a stability monitoring system to achieve the vehicle dynamics control objective. These two strategies use Active Steering and Electro-Mechanical Braking actuators and aim at improving the vehicle stability and steerability by designing a multivariable controller that acts simultaneously on the lateral and longitudinal dynamics of the car. Simulations are performed on a complex nonlinear full vehicle model, the same driving scenario is applied for the two control strategies. The model parameters are those of a Renault Mégane Coupé, obtained by identification with real data. Promising simulations results are obtained. Comparison between the two proposed strategies and the uncontrolled vehicle show the reliability and the robustness of the proposed solutions, even if one is developed within the linear control framework while the other one is a non linear control approach.

A LPV/ℌ ∞ fault tolerant control of vehicle roll dynamics under semi-active damper malfunction

This paper is concerned with the design and analysis of a new multivariable LP V /H∞ (Linear Parameter Varying) robust control design strategy for Global Chassis Control. The main objective of this study is to handle critical driving situations by activating several controller subsystems in a hierarchical way. The proposed solution consists indeed in a two-step control strategy that uses semi-active suspensions, active steering and electro-mechanical braking actuators. The main idea of the strategy is to schedule the 3 control actions (braking, steering and suspension) according to the driving situation evaluated by a specific monitor. Indeed, on one hand, rear braking and front steering are used to enhance the vehicle yaw stability and lateral dynamics, and on the other hand, the semi-active suspensions to improve comfort and car handling performances. Thanks to the LP V /H∞ framework, this new approach allows to reach a smooth coordination between the various actuators, to ensure robustness and stability of the proposed solution, and to significantly improve the vehicle dynamical behavior. Simulations have been performed on a complex full vehicle model which has been validated using data obtained from experimental tests on a real Renault Megane Coupe. Moreover, the suspension system uses Magneto-Rheological dampers whose characteristics have been obtained through experimental identification tests. A comparison between the proposed LPV/H∞ control strategy and a classical LTI/H∞ controller is performed using the same simulation scenarios and confirms the effectiveness of this approach.This paper proposes a new multivariable linear parameter varying (LPV)/H∞ control strategy for global chassis control. The main objective is to handle critical driving situations by activating several subsystems (semi-active suspensions, active steering, and electromechanical braking actuators) in a hierarchical way. The main idea is to schedule the three control actions (braking, steering and suspension) according to the driving situation evaluated by a specific monitor. Indeed, on one hand, rear braking and front steering are used to enhance the vehicle yaw stability and lateral dynamics, and on the other hand, the semi-active suspensions are used to improve comfort and car handling performance. Due to the LPV/H∞ framework, this new approach allows a smooth coordination to be reached between the various actuators, to ensure robustness and stability of the proposed solution, and to significantly improve the vehicle dynamical behavior. Simulations have been performed on a complex full vehicle model, which has been validated using data obtained from experimental tests on a real Renault Mégane Coupé. Moreover, the suspension system uses magnetorheological dampers whose characteristics have been obtained through experimental identification tests. A comparison between the proposed LPV/H∞ control strategy and a classical linear time-invariant/H∞controller is performed using the same simulation scenarios and confirms the effectiveness of this approach.